Abstract
Current methods of measuring heart rate (HR) and oxygen levels (SPO2) require physical contact, are individualised, and for accurate oxygen levels may also require a blood test. No-touch or non-invasive technologies are not currently commercially available for use in healthcare settings. To date, there has been no assessment of a system that measures HR and SPO2 using commercial off-the-shelf camera technology that utilises R, G, B and IR data. Moreover, no formal remote photoplethysmography studies have been done in real life scenarios with participants at home with different demographic characteristics. This novel study addresses all these objectives by developing, optimising, and evaluating a system that measures the HR and SPO2 of 40 participants. HR and SPO2 are determined by measuring the frequencies from different wavelength band regions using FFT and radiometric measurements after pre-processing face regions of interest (forehead, lips, and cheeks) from Colour, IR and Depth data. Detrending, interpolating, hamming, and normalising the signal with FastICA produced the lowest RMSE of 7.8 for HR with the r-correlation value of 0.85 and RMSE 2.3 for SPO2. This novel system could be used in several critical care settings, including in care homes and in hospitals and prompt clinical intervention as required.
Original language | English |
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Article number | 4974 |
Number of pages | 44 |
Journal | Sensors |
Volume | 21 |
Issue number | 13 |
DOIs | |
Publication status | Published - 30 Jun 2022 |
Keywords
- Remote health monitoring
- Heart rate measurement
- Blood oxygenation level measurement
- rPPG system
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Dive into the research topics of 'Automated Remote Pulse Oximetry System (ARPOS)'. Together they form a unique fingerprint.Datasets
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Automated Remote Pulse Oximetry System (ARPOS Code)
Pirzada, P. (Creator), GitHub, 2022
https://github.com/PirehP/ARPOSpublic
Dataset: Software
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Automated Remote Pulse Oximetry System (ARPOS) Dataset
Pirzada, P. (Creator), Harris-Birtill, D. C. C. (Supervisor) & Doherty, G. H. (Supervisor), Zenodo, 6 May 2022
DOI: 10.5281/zenodo.6522389, https://doi.org/10.17630/sta/624
Dataset